class Test(unittest.TestCase):
def setUp(self):
self._test_obj = ForwardSendingMessaging()
self._prev = ForwardSendingMessaging()
self._next = ForwardSendingMessaging()
def test_solver_linking(self):
self._test_obj.link_solvers(previous=self._prev, next=self._next)
self.setUp()
with self.assertRaises(ValueError):
self._test_obj.link_solvers(previous=None, next=self._next)
def test_sending(self):
self._test_obj.link_solvers(previous=self._prev, next=self._next)
_value = "a value"
_flag = Message.SolverFlag.iterating
self._test_obj.send(value=_value, flag=_flag)
self.assertIs(self._next.buffer.value, _value)
self.assertIsNone(self._next.buffer.time_point)
self.assertIs(self._next.buffer.flag, _flag)
def test_receiving(self):
self.assertIsInstance(self._test_obj.receive(), Message)
self.assertIsNone(self._test_obj.receive().value)
self.assertIsNone(self._test_obj.receive().time_point)
def run_problem(real, imag, max_iter, num_steps, num_nodes, criteria, task, num_tasks, n_procs, starttime):
_width = len(str(num_tasks))
_percent = float(task) / float(num_tasks) * 100
_diff_time = time.time() - starttime
_time_epsilon = 0.1
if task > n_procs \
and ((_diff_time > 8.0 and
((_diff_time % 10.0) < _time_epsilon) or ((10.0 - (_diff_time % 10.0)) < _time_epsilon))
or (num_tasks % 2 == 0 and _percent % 4 == 0)
or (num_tasks % 2 != 0 and _percent % 4 == 0)):
print("[ {:6.2f}%] Starting task {:{width}d} of {:{width}d}: \\lambda = {: .3f}{:+.3f}i"
.format(_percent, task, num_tasks, real, imag, width=_width))
problem = LambdaU(lmbda=complex(real, imag))
check = ThresholdCheck(min_threshold=1e-14, max_threshold=max_iter,
conditions=('residual', 'iterations'))
comm = ForwardSendingMessaging()
solver = ParallelSdc(communicator=comm)
comm.link_solvers(previous=comm, next=comm)
comm.write_buffer(value=problem.initial_value, time_point=problem.time_start)
solver.init(integrator=SdcIntegrator, problem=problem, threshold=check, num_time_steps=num_steps, num_nodes=num_nodes)
try:
solution = solver.run(SemiImplicitSdcCore, dt=(problem.time_end - problem.time_start))
return int(solution[-1].used_iterations)
except RuntimeError:
return max_iter + 1
def solve_parallel(prob, _core):
thresh = ThresholdCheck(max_threshold=25,
min_threshold=1e-7,
conditions=('error', 'solution reduction', 'error reduction', 'residual', 'iterations'))
comm = ForwardSendingMessaging()
solver = ParallelSdc(communicator=comm)
comm.link_solvers(previous=comm, next=comm)
comm.write_buffer(value=prob.initial_value, time_point=prob.time_start)
solver.init(integrator=SdcIntegrator, threshold=thresh, problem=prob, num_time_steps=1, num_nodes=3)
sol = solver.run(core=_core, dt=0.5)
print(sol)
def _run_sdc_with_problem(problem, core, num_time_steps, dt, num_nodes, max_iter, precision):
thresh = ThresholdCheck(max_threshold=max_iter + 1, conditions=('error', 'residual', 'solution reduction', 'error reduction', 'iterations'),
min_threshold=1e-7)
_comm = ForwardSendingMessaging()
_sdc = ParallelSdc(communicator=_comm)
_comm.link_solvers(previous=_comm, next=_comm)
_comm.write_buffer(value=problem.initial_value, time_point=problem.time_start)
_sdc.init(integrator=SdcIntegrator, threshold=thresh, problem=problem, num_time_steps=num_time_steps, num_nodes=num_nodes)
_solution = _sdc.run(core, dt=dt)
# for _node_index in range(0, len(_solution.solution(-1))):
# print("Node {}: {} <-> {}".format(_node_index, _solution.solution(-1)[_node_index].value, problem.exact(_solution.solution(-1)[_node_index].time_point)))
# assert_numpy_array_almost_equal(_solution.solution(-1)[_node_index].value,
# problem.exact(_solution.solution(-1)[_node_index].time_point),
# places=2)
assert_true(len(frozenset(thresh.has_reached()).intersection(frozenset(('error', 'solution reduction', 'error reduction', 'residual')))) > 0,
"Termination criteria should be 'error' or 'residual'.")
assert_not_in('iterations', thresh.has_reached(), "Maximum Number of iterations should not be reached.")
def setUp(self):
self._test_obj = ForwardSendingMessaging()
self._prev = ForwardSendingMessaging()
self._next = ForwardSendingMessaging()